This relates to multi-channel radar, and more particularly to radar that employ polarization diversity to develop the multiple channels.
There are many proposals for multi-channel radar, emanating from the conventional monostatic radar system where transmitter and receiver are collocated. Collocation makes it easy for transmitter and receiver to share a common stable clock (local oscillator), which is required for both range and Doppler measurements. Signal processing for multi-static radars with widely dispersed antenna elements is currently a very active research area, in part because of significant advances in hardware capabilities, and certainly because multi-static radar enables multiple views of a scene, and a (wide angle) tomographic approach to the recovery of the scene from received data. A substantial improvement in detection results from the availability of multiple views of the target. When system elements are widely dispersed, however, the coherent implementation of multi-static radar is difficult because of clock synchronization problems, though GPS and network technologies have rendered these problems more tractable. An additional challenge of multi-static radars is the degree of computation that is necessary to recover the scene, or detect a target, by integrating multiple views.
It is natural to approach multi-channel radar in terms of spatial diversity concepts developed for multiple-input-multiple-output (MIMO) communications where performance improvement result from the statistical independence of the different channels provided by the spatially separated multiple antenna elements.
Polarimetric radar transmits radio wave pulses that have both horizontal and vertical polarizations. In weather prediction applications, for example, the horizontal pulses essentially give a measure of the horizontal dimension of clouds (cloud water and cloud ice) and precipitation particles (snow, ice pellets, hail, and rain), while the vertical pulses essentially give a measure of the vertical dimension. Since the power returned to the radar is a complicated function of each particles size, shape, and ice density, this additional information results in improved estimates of rain and snow rates, better detection of large hail location in summer storms, and improved identification of rain/snow transition regions in winter storms. The success of polarimetric radar in discriminating diverse regions in radar images demonstrates the value of using all dimensions of the polarization scattering matrix and motivates the use of polarimetry for target detection in a dynamic clutter environment.
Current polarimetric radar systems are capable of serial transmission using two orthogonal polarizations. Typically the radar separates the two orthogonal polarizations by transmitting a waveform on one polarization followed by a second waveform on the orthogonal polarization. The radar receiver accepts signals of both polarizations at all times, but systems that transmit the different polarizations seriatim are not able to form an instantaneous measurement of the fall scattering matrix. It is expected, however, that improved operation (i.e. more robust detections) can be attained by forming such instantaneous measurements and deriving the full scattering matrix.